/**
 * ONNX Local Embeddings (Feature 7)
 *
 * 100% offline, no API key needed
 * Uses ONNX Runtime to run Sentence-BERT models locally
 *
 * Setup:
 * 1. npm install onnxruntime-node
 * 2. Download model: all-MiniLM-L6-v2 ONNX format
 */
import type { Embedder } from '../embeddingPipeline.js';
export interface ONNXEmbedderConfig {
    /** Path to the ONNX model file */
    modelPath?: string;
    /** Maximum sequence length (default: 256) */
    maxLength?: number;
    /** Embedding dimensions (depends on model, default: 384) */
    dimensions?: number;
}
/**
 * ONNX-based local embedder
 * Runs entirely on your machine - no API calls!
 */
export declare class ONNXEmbedder implements Embedder {
    private modelPath;
    private maxLength;
    private dimensions;
    private session;
    private initialized;
    constructor(config?: ONNXEmbedderConfig);
    private initialize;
    embedText(text: string): Promise<Float32Array>;
    embedDiff(diff: string): Promise<Float32Array>;
    private getEmbedding;
    /**
     * Simple fallback embedding when ONNX is not available
     * Uses character-based hashing - good enough for testing
     */
    private fallbackEmbedding;
}
/**
 * Create ONNX embedder from environment variables
 */
export declare function createONNXEmbedder(): ONNXEmbedder;
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